- Increased the client’s CTR by 29.65 %: From 3.44 % to 4.46 %
- Decreased the CPC by 40%
Dermeze sells a range of moisturising products for dry, sensitive skin. From Moisturising Soap Free Wash, to Moisturising Lotion, Cream, or Ointment. Their cream is a hypoallergenic and fragrance-free, gentle moisturiser suitable for every-day use to replenish dry and sensitive skin on the face and body.
Dermeze is a brand owned by Aspen Pharmacare Australia and is classified as a pharmaceutical range of products. It is always a big challenge to advertise pharmaceutical products on Google, as Pharmaceutical manufacturers must be certified by Google in order to serve ads.
For Dermeze we don’t target branded keywords as the branded keywords have a strong organic position and therefore Dermeze has made a business decision to use this budget in our other campaigns. The monthly spend is directed towards keywords targeting symptoms and products associated with dry skin, as well targeting competitor keywords.
How we increased Dermeze’s PPC CTR by 29.65 %, and lowered their Google Ads CPC by 38.47 % from 1 of June 2018 until end of April 2019.
This case study shows how through restructuring the campaign/ ad group
set ups, sound analysis and taking swift and informed action we achieved such great results for Dermeze.
We restructured the account based on the different keyword phrases, through using the different keyword match types on a campaign level. Previously the account was set up using only broad modified and exact match keywords but we decided to test the performance of phrase match keywords as well. With phase match keywords we could reach lower CPC and CTR; and the average cost/conversion was lower than broad modified or exact match keywords.
We used cross exclusions to prevent our keywords from competing against each other. We also frequently checked the search terms which were generated by the new exact match keywords.
We compared the search terms with the list which was generated by the script and we excluded the irrelevant phrases and we used cross exclusions.
We significantly increased the number of negative keywords and extended the negative keyword lists previously created, excluding irrelevant general phrases eg: phrases which related to death, animals’ names and so on.
We added location targeting to break-down performance by states and Australia’s most populated cities. This enabled us to make bid adjustments on a location level. We also implemented ad schedules to be able to make bid adjustments for the better performing times of the day. Lastly, we also used bid adjustments for devices on an ad group level.
We uploaded extension such as sitelink, call-out, and structured snippet extensions on campaign level to increase the quality score of the keywords and increase the coverage on The Google Search Network.
We tested different bid strategies as well, especially and most significantly, a Maximise conversions bid strategy. Our main goal was to decrease the cost/conversion and increase the number of conversions, whilst following the same budget. This account didn’t have conversion measurement set-up when we took over managing the account. That is why this case study is about CPC and CTR instead of cost/conversion or conversions.
As the product page is not consistent with an e-commerce website. To judge performance, we measure specific actions taken on the site. Which are: users who click on the store finder button, users who search for a post code and users who click on the retailer’s button.
The following graph shows the trend of the CTR% from April 2018 until the end of April 2019. Note, we only started on the account from the 1st June 2018. However, to highlight the improved performance of the account we are including a date range of 1 calendar year.